From Causes for Database Queries to Repairs and Model-Based Diagnosis and Back
arXiv:1412.4311
Abstract
In this work we establish and investigate connections between causality for query answers in databases, database repairs wrt. denial constraints, and consistency-based diagnosis. The first two are relatively new problems in databases, and the third one is an established subject in knowledge representation. We show how to obtain database repairs from causes and the other way around. Causality problems are formulated as diagnosis problems, and the diagnoses provide causes and their responsibilities. The vast body of research on database repairs can be applied to the newer problem of determining actual causes for query answers and their responsibilities. These connections, which are interesting per se, allow us, after a transition -inspired by consistency-based diagnosis- to computational problems on hitting sets and vertex covers in hypergraphs, to obtain several new algorithmic and complexity results for causality in databases.
Extended version of paper to appear in Proceedings of ICDT 2015
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Cited by in corpus (5)
- The Shapley Value of Tuples in Query Answering
- Quantifying Causal Effects on Query Answering in Databases
- From Checking to Inference: Actual Causality Computations as Optimization Problems
- Causes for Query Answers from Databases, Datalog Abduction and View-Updates: The Presence of Integrity Constraints
- ZaliQL: A SQL-Based Framework for Drawing Causal Inference from Big Data